Nisha Kanwar
Impact in
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- Cancer Genomics and Diagnostics
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- Cancer Cells and Metastasis
- Peptidase Inhibition and Analysis
Papers in
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- RNA and protein synthesis mechanisms 3
- Protein Degradation and Inhibitors 2
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- Sarcoma Diagnosis and Treatment 3
- Metastasis and carcinoma case studies 3
- Co-authors
- Susan J. Done (7 shared papers)David R. McCready (3 shared papers)Pingzhao Hu (2 shared papers)Mark Clemons (1 shared paper)Philippe L. Bédard (2 shared papers)Burckhard Seelig (2 shared papers)Dawei Ma (1 shared paper)Jan Jongstra (1 shared paper)
- Journals
- Cancer Research (4 papers)Nucleic Acids Research (3 papers)Molecular Cancer Therapeutics (1 paper)Scientific Reports (1 paper)Pediatric Blood & Cancer (1 paper)
- Partner nations
- CanadaUnited KingdomUnited States
In The Last Decade
Nisha Kanwar
19 papers receiving 264 citations
Peers
Comparison fields: 5 of 57
- Cancer Research 72
- Oncology 89
- Pathology and Forensic Medicine 48
- Molecular Biology 149
- Genetics 21
Countries citing papers authored by Nisha Kanwar
This map shows the geographic impact of Nisha Kanwar's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Nisha Kanwar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nisha Kanwar more than expected).
Fields of papers citing papers by Nisha Kanwar
This network shows the impact of papers produced by Nisha Kanwar. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Nisha Kanwar. The network helps show where Nisha Kanwar may publish in the future.
Co-authors
The 25 scholars most cited alongside Nisha Kanwar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 54 | |
| 2 | 2010 | 43 | |
| 3 | 2012 | 32 | |
| 4 | 2020 | 30 | |
| 5 | 2018 | 23 | |
| 6 | 2018 | 20 | |
| 7 | 2021 | 19 | |
| 8 | 2015 | 16 | |
| 9 | 2022 | 8 | |
| 10 | 2017 | 5 | |
| 11 | 2020 | 3 | |
| 12 | 2016 | 3 | |
| 13 | 2022 | 3 | |
| 14 | 2023 | 2 | |
| 15 | 2017 | 2 | |
| 16 | 2023 | 1 | |
| 17 | 2013 | 1 | |
| 18 | 2013 | 1 | |
| 19 | 2013 | 1 | |
| 20 | 2021 | 0 |
About Nisha Kanwar
Nisha Kanwar is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Oncology, Cancer Research and Ecology, having authored 23 papers that have together received 267 indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (7 papers), Cancer Cells and Metastasis (4 papers), Bacteriophages and microbial interactions (3 papers), Sarcoma Diagnosis and Treatment (3 papers), RNA and protein synthesis mechanisms (3 papers), Metastasis and carcinoma case studies (3 papers), Protein Degradation and Inhibitors (2 papers) and Bacterial Genetics and Biotechnology (2 papers). The work is most often cited by research in Cancer Research (72 citations), Oncology (89 citations), Pathology and Forensic Medicine (48 citations), Molecular Biology (149 citations) and Genetics (21 citations). Nisha Kanwar has collaborated with scholars based in Canada, United Kingdom and United States. Frequent co-authors include Susan J. Done, David R. McCready, Pingzhao Hu, Mark Clemons, Philippe L. Bédard, Burckhard Seelig, Dawei Ma, Jan Jongstra, Xiujie Liu and Irene A. Chen. Their work appears in journals such as Cancer Research, Nucleic Acids Research, Molecular Cancer Therapeutics, Scientific Reports and Pediatric Blood & Cancer.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.